I'm assuming this article is meant for the general public and not people in specific industry but I don't know what generalization means in this context and this article does a piss poor job of explaining it. Constantly repeating "generalization of learning" doesn't get me any closer to understanding.
Generalization is standard lingo in machine learning – it's about going from known data (training set / test set) to new data which shares the same underlying patterns but wasn't available at learning time.
Taking the posts simple polynomial example, it would be going from
4x^2 + 2x -3 = 0
to
2x^2 -5x +2 = 0
or more generally to
ax^2 + bx + c = 0
I mean, just the standard dictionary meaning of generalization works just fine here, no? I had no problems following the article.
The intended audience is people who are knowledgeable about spaced repetition, and such people typically know what generalization means in the context of learning.
Could this work for training AI? Has anyone tried?